Vertical axis wind turbines (VAWTs) are very attractive for in-home power generation since they can be adopted even at low wind speeds and highly variable wind direction. Even if significant experimental research activity has been carried out to improve VAWTs performance, the ability to accurately reproduce flow field characteristics around turbine blades by CFD (computational fluid dynamics) techniques represents a powerful approach to further enhance wind turbines performance. Thanks to CFD, in fact, it is possible to reproduce flow characteristics with a detail level impossible to achieve by experiments. Nevertheless, in order to appropriately analyze the flow structure by CFD application, an accurate validation is essential, and high-quality measurements of some main flow characteristics are required. In recent publications the authors investigated, both experimentally and numerically, the performance of an innovative double bladed Darrieus-type VAWT, with the aim to define an optimal configuration also focusing on self-starting ability of the prototype by employing CFD technique. Nevertheless, comparison between experiments and numerical results was made only in terms of power and torque coefficients. To overcome such limitation, in this paper the authors propose an experimental benchmark case for CFD results validation, describing detailed flow field in correspondence of one pair of blades of the innovative Darrieus-type VAWT in static conditions. Measurements were performed employing Particle Image Velocimetry (PIV) technique on a scaled model of the turbine blades realized by 3D printing. An uncertainty analysis was also performed which showed a high accuracy of the obtained experimental results. The measurements of the main flow characteristics (bi-dimensional velocity components) were then used for a test case CFD validation of two different turbulence models.

PIV measurements over a double bladed Darrieus-type vertical axis wind turbine: A validation benchmark

Arpino F.;Cortellessa G.
;
Scungio M.;Frattolillo A.
2021-01-01

Abstract

Vertical axis wind turbines (VAWTs) are very attractive for in-home power generation since they can be adopted even at low wind speeds and highly variable wind direction. Even if significant experimental research activity has been carried out to improve VAWTs performance, the ability to accurately reproduce flow field characteristics around turbine blades by CFD (computational fluid dynamics) techniques represents a powerful approach to further enhance wind turbines performance. Thanks to CFD, in fact, it is possible to reproduce flow characteristics with a detail level impossible to achieve by experiments. Nevertheless, in order to appropriately analyze the flow structure by CFD application, an accurate validation is essential, and high-quality measurements of some main flow characteristics are required. In recent publications the authors investigated, both experimentally and numerically, the performance of an innovative double bladed Darrieus-type VAWT, with the aim to define an optimal configuration also focusing on self-starting ability of the prototype by employing CFD technique. Nevertheless, comparison between experiments and numerical results was made only in terms of power and torque coefficients. To overcome such limitation, in this paper the authors propose an experimental benchmark case for CFD results validation, describing detailed flow field in correspondence of one pair of blades of the innovative Darrieus-type VAWT in static conditions. Measurements were performed employing Particle Image Velocimetry (PIV) technique on a scaled model of the turbine blades realized by 3D printing. An uncertainty analysis was also performed which showed a high accuracy of the obtained experimental results. The measurements of the main flow characteristics (bi-dimensional velocity components) were then used for a test case CFD validation of two different turbulence models.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/89226
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